Search

Background: The evaluation of tumor differentiation is an urgent clinical issue that would facilitate the establishment of individualized therapeutic strategies. Our aims were to develop a deep learning radiomics model based on computed tomography (CT) data for preoperative evaluation of hepatocellular carcinoma (HCC) differentiation (low vs high grade), and to preliminarily explore the biological basis of the radiomics model. Methods: A total of 1234 HCC patients with contrast-enhanced CT images were recruited from two institutions. Radiomics features were extracted from preoperative venous-phase CT data and selected in terms of reproducibility, relevance, and redundancy. The random forest (RF) algorithm was applied to establish a radiomics signature. Meanwhile, the deep learning model was constructed based on a VGG network. Additionally, clinical characteristics of the subjects were used to construct a clinical model. Finally, the fused model integrated a tripartite prediction based on a logistic regression algorithm. A correlation analysis was performed to explore the association between radiomics features and biological variables based on multiomics levels. Findings: The radiomics signature established with the RF algorithm comprised 25 radiomics features. The AUCs in the training, internal validation, and independent test cohorts were 0·82, 0·76, and 0·75, respectively, for the radiomics signature; 0·85, 0·81, and 0·75, respectively, for the deep learning model; and 0·89, 0·83, and 0·80, respectively, for the fused model. Multiomics analysis showed that the selected radiomics features contained abundant biological information that was related to tumor differentiation. Interpretation: Our deep learning radiomics model can serve as a noninvasive tool of preoperative HCC differentiation evaluation to guide clinical decision-making and prognostic stratification. Funding: National Key Research and Development Program of China, Natural Science Foundation of China, Zhejiang Provincial Education Department. Declaration of Interest: The authors declare that they have no competing interests. Ethical Approval: This study was approved by the institutional review boards of the First Affiliated Hospital, College of Medicine, Zhejiang University (Institution 1) and Ningbo Medical Center Lihuili Hospital (Institution 2), which waived the requirement for patients’ informed consent.

Fibrosis is the common endpoint and currently the best predictor of progression of chronic kidney diseases (CKD). Despite several drawbacks, biopsies remain the only available means to specifically assess the extent of renal fibrosis. Here we show that molecular imaging of the extracellular matrix protein elastin allows for non-invasive staging and longitudinal monitoring of renal fibrosis. Elastin was hardly expressed in healthy mouse, rat, and human kidneys, whereas it was highly upregulated in cortical, medullar, and perivascular regions in progressive CKD. Compared to a clinically relevant control contrast agent, the elastin-specific magnetic resonance imaging (MRI) agent ESMA specifically detected elastin expression in multiple mouse models of renal fibrosis, and also in fibrotic human kidneys. Elastin imaging allowed for repetitive and reproducible assessment of renal fibrosis, and it enabled longitudinal monitoring of therapeutic interventions, accurately capturing anti-fibrotic therapy effects. Finally, in a model of reversible renal injury, elastin imaging detected ensuing fibrosis not identifiable via routine assessment of kidney function. Elastin imaging thus has the potential to become the first non-invasive, specific imaging method to assess renal fibrosis.

An entire network may move as a unit and change its point of attachment to the Internet dynamically. To support this kind of network mobility, a Network Mobility Basic Support Protocol for IPv6 (NEMOv6) has been proposed by IETF. This paper analyzes the characteristics of IPv6-based network mobility management, and simulates handoff performance of a Mobile Router (MR) with a subnet, including one or more Mobile Nodes (MN) which move in various scenarios. Based on the simulation results, we demonstrate the impact of average moving speed rate and average data transmission rate to the performance of mobile network. Moreover, a Linux OS based network mobility experiment platform was established to evaluate the practical handoff performance of the MR using FTP service. Lastly, future work of network mobility management is proposed.

To support mobile nodes moving across different networks as a whole, the IETF NEMOv6 (RFC 3963) has been proposed. Compared with Mobile IPv6 protocol, the NEMOv6 provides a method to enable a network moving entirely. Mobile Router (MR) is introduced to the NEMOv6, which performs mobility management function for the entire mobile network. All nodes belonged to the mobile network, fixed or mobile, are hidden by the MR when the network moving. The NEMOv6 protocols have many advantages that it can reduce the cost of network access signaling, network bandwidth and radio resources occupied. This paper analyzes the characteristics of network mobility protocols in IP networks, and simulates handoff performance of a Mobile Router (MR) with a subnet by changing the number of MNs. Based on the simulation results, we demonstrate the impact of mobile network scale and illustrate its superiority to MIPv6. Furthermore, a Linux OS based network mobility experiment platform was established to evaluate the practical handoff performance of LMN as well as VMN. Lastly, future work of network mobility management is proposed.

With the development of wireless communication technologies and mobile Internet, the demand for the ubiquitous service is increasing dramatically. However, there are many critical issues which prevent the performance in accessing the ubiquitous heterogeneous wireless networks. So the subject has become the focus of many research institutions. We establish a practical testbed which includes the different wireless access network technologies: WLAN, GPRS and TD-SCDMA. In our experiment, the Mobile Node (MN) is a multi-interface device supporting Mobile IPv6 (MIPv6). We implement the MN vertical handoff and evaluate the performance of MN vertical handoff in terms of the handoff delay.

Mobile IPv6 performs mobility management to mobile node within IPv6 networks. Since IPv6 is not widely deployed yet, it’s an important feature to let Mobile IPv6 support mobile node moving to IPv4 network and maintaining the established communications. DSMIPv6 specification extends Mobile IPv6 capabilities to allow dual stack mobile nodes to move within IPv4 and IPv6 networks. This paper describes the implementation of this feature based on open source MIPL under Linux. By performing experiments on testbed using the implementation, it is confirmed that the DSMIPv6 works as expected.